Course Website Locator: 0813

Harvard College/Graduate School of Arts and Sciences

The following course websites match your request:

Spring 2011-2012

Introduction to Econometrics
James H. Stock (fall term) and Eric Chaney (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data,

Fall 2011-2012

Introduction to Econometrics
James H. Stock (fall term) and Eric Chaney (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data,

Spring 2010-2011

Introduction to Econometrics
James H. Stock (fall term) and Eric Chaney (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

Fall 2010-2011

Introduction to Econometrics
James H. Stock (fall term) and Eric Chaney (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

Spring 2009-2010

Introduction to Econometrics
Eric Chaney (fall term) and Guido W. Imbens (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

Fall 2009-2010

Introduction to Econometrics
Eric Chaney (fall term) and Guido W. Imbens (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

Spring 2008-2009

Introduction to Econometrics
Raffaella Giacomini (UCLA and UCL) (fall term) and Keisuke Hirano (University of Arizona) (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

Fall 2008-2009

Introduction to Econometrics
Raffaella Giacomini (UCLA and UCL) (fall term) and Keisuke Hirano (University of Arizona) (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

Spring 2007-2008

Introduction to Econometrics
James H. Stock (fall term) and Rustam Ibragimov (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

Fall 2007-2008

Introduction to Econometrics
James H. Stock (fall term) and Rustam Ibragimov (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

Spring 2006-2007

Introduction to Econometrics
James H. Stock (fall term) and Rustam Ibragimov (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

Fall 2006-2007

Introduction to Econometrics
James H. Stock (fall term) and Rustam Ibragimov (spring term)

An introduction to multiple regression techniques with focus on economic applications. Discusses extensions to discrete response, panel data, and time series models, as well as issues such as omitted variables, missing data, sample selection, randomized and quasi-experiments, and instrumental variables. Aims to provide students with an understanding of and ability to apply econometric and statistical methods using computer packages.

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